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---
title: ML Prediction API
emoji: 🔮
colorFrom: green
colorTo: blue
sdk: docker
app_port: 7860
pinned: false
tags:
- fastapi
- xgboost
- machine-learning
- postgresql
license: mit
---
# ML Prediction API
Production-ready POC for serving an XGBoost model via FastAPI with PostgreSQL logging.
## Features
- **FastAPI**: High-performance API with automatic validation.
- **PostgreSQL**: Persistent logging of all inputs and predictions.
- **XGBoost**: Efficient model inference.
- **Docker**: Containerized for easy deployment.
- **CI/CD**: Automated testing and deployment via GitHub Actions.
- **Authentication**: Simple API Key protection.
## Installation
### Prerequisites
- Docker
- Python 3.10+
- PostgreSQL (if running locally without Docker Compose)
### Local Setup
1. **Clone the repository**
```bash
git clone <repo-url>
cd <repo-name>
```
2. **Install Dependencies**
```bash
pip install -r requirements.txt
```
3. **Environment Variables**
Create a `.env` file or set variables:
```bash
export DATABASE_URL="postgresql://user:password@localhost:5432/dbname"
export API_KEY="your-secret-key"
export MODEL_PATH="02_xgb_model_tuned.pkl"
```
4. **Initialize Database**
```bash
python scripts/create_db.py
```
5. **Run the API**
```bash
uvicorn app.main:app --reload
```
## API Documentation
Once running, visit:
- Swagger UI: `http://localhost:8000/docs`
- ReDoc: `http://localhost:8000/redoc`
### Endpoints
- `POST /predict`: Make a prediction. Requires `X-API-KEY` header.
- `GET /health`: Health check.
- `GET /model/info`: Model metadata. Requires `X-API-KEY` header.
## Deployment
### Hugging Face Spaces
This project is configured to deploy to Hugging Face Spaces using Docker.
1. Create a new Space on Hugging Face (Select Docker SDK).
2. Add the following Secrets in the Space settings:
- `DATABASE_URL`: Connection string to your external PostgreSQL database.
- `API_KEY`: Your desired API key.
3. The GitHub Action `ci-cd.yml` will automatically deploy changes from the `main` branch.
## Architecture
- **app/main.py**: Entry point.
- **app/routers**: API route definitions.
- **app/services**: Business (ML inference).
- **app/models**: Database and Pydantic models.
- **app/core**: Configuration and DB setup.
## Testing
Run tests with coverage:
```bash
pytest --cov=app tests/
```
GLHF ! |